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US Criminal Justice Policy and Practice in the

Twenty-First Century: Toward the End of Mass

Incarceration?

KATHERINE BECKETT, LINDSEY BEACH, EMILY KNAPHUS, and

ANNA REOSTI

Although the wisdom of mass incarceration is now widely questioned, incarceration rates have fallen far less than what would be predicted on the basis of crime trends. Informed by institutional studies of path dependence, sociolegal scholarship on legal discretion, and research suggesting that “late mass incarceration” is characterized by a moderated response to nonviolent crime but even stronger penalties for violent offenses, this article analyzes recent sentencing-related reforms and case processing outcomes. Although the legislative findings reveal widespread willingness to moder-ate penalties for nonviolent crimes, the results also reveal a notably heightened system response to both violent and nonviolent crimes at the level of case processing. These findings help explain why the decline in incarceration rates has been notably smaller than the drop in crime rates and are con-sistent with the literature on path dependence, which emphasizes that massive institutional develop-ments enhance the capacity and motivation of institutional actors to preserve jobs, resources, and authorities. The findings also underscore the importance of analyzing on-the-ground case processing outcomes as well as formal law when assessing the state and fate of complex institutional develop-ments such as mass incarceration.

I. INTRODUCTION

The dramatic expansion of the US penal system in recent decades has stimulated much research regarding the causes and consequences of this unprecedented development. Studies show that shifts in policy and practice, rather than increases in the crime rate, were the primary driver of penal expansion (Neal and Rick 2014; Travis, Western, and Redburn 2014; Raphael and Stoll 2009, 2013; PEW Center on the States 2012; Western 2006; Blumstein and Beck 1999). Specifically, changes in the exercise of police and prose-cutorial discretion—and especially the effort to identify and punish drug law violators— explain much of the rise in incarceration rates (Travis, Western, and Redburn 2014; Blumstein and Beck 1999). Increasingly long sentences and prison stays, especially for violent crimes, have also contributed importantly to mass incarceration (Travis, West-ern, and Redburn 2014; Raphael and Stoll 2009, 2013; PEW Center on the States 2012; Western 2006).

Thanks to Bruce Western and to participants in the University of Washington Department of Sociology’s devi-ance seminar, particularly Charlie Hirschman, for useful feedback on an early version of this article. This research was supported by the National Science Foundation’s Law and Social Sciences program (#1456180).

Address correspondence to: Katherine Beckett, University of Washington—Law, Societies & Justice, Box 353565, Seattle, WA 98115, USA. Telephone: 206-543-4461; E-mail: [email protected].

LAW & POLICY, Vol. 40, No. 4, October 2018ISSN 0265-8240

doi: 10.1111/lapo.12113

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The consequences of mass incarceration, including its highly disparate impact on communities of color (Lee et al. 2015; Alexander 2010; Clear 2007; Pettit and Western 2004) and its adverse effects on affected families and communities (Wakefield, Lee, and Wildeman 2016; Lee et al. 2014, 2015; Sykes and Pettit 2014; Wakefield and Wildeman 2013; Wildeman and Western 2010; Clear 2007; Comfort 2007; Western 2006), are of great sociological significance. Penal expansion affects not only the incarcerated but also those who are stopped, frisked, arrested, fined, and surveilled (Harris 2016; Greenberg, Meredith and Morse 2016; Sewell, Jefferson, and Lee 2016; Stuart, Amenta, and Osborne 2015; Napatoff 2015; Brayne 2014; Kohler-Hausmann 2013; Beckett and Harris 2011; Rios 2011; Harris, Evans, and Beckett 2010). Studies also indicate that mass incarceration has had far-reaching demographic, political, and sociological effects that tend to enhance—and mask—racial and socioeconomic inequalities (Wakefield, Lee, and Wildeman 2016; Lee et al. 2014; Travis, Western, and Redburn 2014; Pettit 2012; Western 2006, 2012; Harris, Evans, and Beckett 2010; Pettit and Western 2004; Western and Beckett 1999).

Although the policies, practices, and discourses that fueled mass incarceration enjoyed decades of widespread support,1 the situation has changed notably in recent years. US incarceration rates have declined modestly since 2007, and at least forty-eight states and the District of Columbia have undertaken some type of criminal justice reform aimed at reducing incarceration (Subramania and Moreno 2014). A notable shift in public discourse has also occurred (Beckett, Reosti, and Knaphus 2016; Opportunity Agenda 2014). These developments are partly the result of the mobilization of conserva-tive critics of mass incarceration who “tied what had been a handful of scattered state-level reforms into a broader narrative that cast decarceration as a matter of conservative principle, then marshaled their political networks to spread the message, and plotted strategic initiatives at the state and federal levels to bring around potential allies” (Dagan and Teles 2014, 270; see also Dagan and Teles 2016).

Despite these important political and cultural shifts, as well as plummeting crime rates, the imprisonment rate had fallen by just 11 percent by 2016, and the United States remains the world’s leading jailer (Wagner and Walsh 2016). In fact, from 2007 to 2016, the index crime rate fell more than twice as much as the imprisonment rate (24.3 vs. 11.1 percent).2 In this context, analysts have offered various interpretations of the nature— and persistence—of “late” mass incarceration. Drawing on theories of path dependence, some scholars emphasize the importance of new or expanded interest and professional groups that benefit economically or politically from mass incarceration and the ways in which these groups exercise their political influence to maintain the penal status quo (Gottshalk 2015; Thorpe 2015; Page 2011). On the other hand, Seeds (2016) and others (Beckett, Reosti, and Knaphus 2016) highlight the recent emergence of a new way of thinking and talking about crime, one that sharply differentiates nonviolent from violent offenses. Seeds (2016) argues that this bifurcation is a defining feature of “late mass incarceration,” one that explains why many states enacted or broadened statutes that allow for life-without-the-possibility-of-parole sentences even as they scaled back penal-ties for nonviolent crimes.

Although these interpretations differ, both focus on sentencing law as the primary measure of penal change. By contrast, sociolegal scholars emphasize that formal law’s institutional effects are powerfully shaped by the “street-level bureaucrats” who shape law’s meaning and effects though their everyday decision making (Ulmer and Johnson 2017; Lynch 1998, 2016; Verma 2016; Lynch and Omori 2014; Bushway and Forst 2013; Halliday et al. 2009; Johnson, Ulmer, and Kramer 2008; Maynard-Moody and Musheno 2003; Silbey and Sarat 1987; Lipsky 1980). Sociolegal scholarship thus

Beckett et al. TOWARD THE END OF MASS INCARCERATION?323

underscores the need to analyze “law in action” as well as “law on the books” when assessing the contemporary criminal justice field.

In this article, we analyze trends in criminal justice policy and in case processing from 2007, when incarceration rates peaked and the Great Recession began, through 2014. We do so to address three main research questions. First, are contemporary trends in legislation and case processing working to sustain exceptionally high incarceration rates? Second, are these trends consistent with the bifurcation hypothesis? Finally, to the extent that the bifurcation hypothesis does not explain these developments, what does the pat-tern of results reveal about the persistence of mass incarceration?

Throughout the analysis, we treat legislative developments and criminal justice case processing outcomes as two potentially quite distinct windows on to the contempo-rary penal landscape. Our goal is not to assess whether legislation is achieving its intended effects in particular states. Rather, we provide a comprehensive assessment of the bifurcation hypothesis, which suggests that both sentiments about, and penal-ties for, people convicted of nonviolent offenses are increasingly lenient, while those pertaining to violent crimes are increasingly punitive (Seeds 2016). In theory, the shift-ing sensibilities regarding violent and nonviolent crime highlighted by those advancing the bifurcation hypothesis could impact both the development of formal law, as Seeds (ibid.) emphasizes, and the informal exercise of discretion by institutional actors. As Maynard-Moody and Musheno (2003) point out, frontline government workers bal-ance the demand that they follow laws, rules, and administrative procedures against their assessments of the moral character of the people with whom they interact. Indeed, as Maynard-Moody and Musheno suggest, these decision makers often make decisions about who the “bad guys” are and interact with them based on this moral assessment: “Once someone is labelled as a ‘bad guy,’ every infraction of the rules, every character flaw, is used to limit service, to punish even slight misdeeds, and to confirm the street-level workers’ moral judgment of the individual” (ibid., 143). To the extent that the cultural sensibilities postulated by the bifurcation hypothesis are operative, prosecutors and judges may be increasingly open to diversion for people convicted of certain drug and property crimes but also increasingly committed to pun-ishing people convicted of violent offenses more harshly.

On the other hand, other, more pragmatic factors—especially the institutional incen-tives noted by theorists of path dependence—may be shaping case processing outcomes in less normative and offense-specific ways. For example, if prosecutors or other front-line criminal justice professionals are motivated mainly to retain their resources and authority, they may be intensifying their response to all forms of criminal wrongdoing and not only to allegations of violence. Analyzing trends in both law on the books and case processing outcomes by offense type will enable us to assess the degree to which any changes observed are consistent with the bifurcation hypothesis, or, alternatively, with theoretical perspectives that emphasize the importance of path dependence and institutional incentives. This comprehensive analysis also enables us to identify policies and practices that are working to sustain high incarceration rates in the context of dra-matically falling crime rates.

This article is organized as follows. Part II provides some historical background, high-lights the importance of analyzing law-in-action as well as formal law, and describes var-ious theoretical perspectives on the factors that may influence the exercise of legal discretion. Part III describes the data and methods used in our analyses. The results are presented in Part IV. The conclusion considers the empirical and theoretical implications of our findings.

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II. THE END OF MASS INCARCERATION? MAKING SENSE OF CONTEMPORARY CRIMINAL

JUSTICE POLICY AND PRACTICE

Mass incarceration’s causes and consequences have been studied extensively (for a recent overview, see Travis, Western, and Redburn 2014). While policy, practice, and rhetoric shifted mainly in a punitive direction during the prison buildup, developments since mass incarceration’s peak in 2007 are comparatively opaque and complex. At the legisla-tive level, many states have enacted measures intended to reduce reliance on prisons and jails, in part due to budget constraints stemming from the Great Recession (Phelps and Pager 2016; Aviram 2015; Brown 2013) as well as the mobilization of conservative reformers (Dagan and Teles 2014, 2016). Yet punitive rhetoric and lawmaking also per-sist (Beckett, Reosti, and Knaphus 2016; Seeds 2016; Gottshalk 2015), particularly with respect to violent crime, and most of the harsh sentencing laws that fueled penal expan-sion remain on the books (Tonry 2016).

Much of what is known about recent legislative developments comes from reports produced by researchers at the Vera Institute, the Sentencing Project, PEW Charitable Trusts, and the National Conference of State Governments (see PEW Charitable Trusts 2016; Silber, Subramanian and Spotts 2016; Porter 2011–2013, 2014, 2015; Subramanian and Delaney 2014; Subramanian and Moreno 2014; Lawrence 2013; Austin 2011; King 2008, 2009). Although these reports provide useful information about recent decarcera-tive reforms, they often do not include legislation intended to increase the severity of punishment. As a result, these reports, if considered alone, may be misleading. Indeed, there is evidence that some states continued to enact punitive criminal policies after 2007 (Beckett, Reosti, and Knaphus 2016). Similarly, Seeds (2016) finds that many states expanded their life-without-parole (LWOP) statutes even as they adopted drug law reform and other decarcerative legislation aimed at low-level offenses.

Based in part on these findings, Seeds (ibid., 1) argues that “contemporary penal pol-icy is better characterized as a bifurcation, responding uniquely . . . to the dilemmas and constraints of ‘late mass incarceration.’” According to Seeds, the logic of bifurcation— which holds that the response to nonviolent crime should fundamentally differ from the response to violent crime—is the guiding principle of the current reform movement, one that increasingly shapes both discourse and policy. Seeds (2016) shows that statutes that authorize or expand LWOP sentences have proliferated in states that have also embraced sentencing reform for nonviolent offenses. From this perspective, the fact that states have continued to expand LWOP statutes even while enacting decarcerative reforms aimed at nonviolent offenses is evidence not of chaos and contradiction but of bifurcation.

The potential racial implications of bifurcation, to the extent that it is occurring, are unclear. Although drug reform is often seen as a means of reducing racial disproportion-ality, people of color, and especially African Americans, are overrepresented among those convicted of both drug crimes and violent offenses. For example, at the end of 2015, 35.6 percent of those serving time in state prison for a violent offense, and 31.2 percent of those serving time for a drug crime, were black (Carson 2018, Table 13). Fur-ther complicating matters, these categories (i.e., “drug” and “violent”) are best under-stood as fluid rather than as fixed. Indeed, prominent conservatives have recently argued that selling drugs is an inherently violent act (Bennett and Walters 2016). In this context, some states have reclassified drug sales as a violent crime, and a number have introduced or expanded legislation that would enable prosecutors to file homicide charges against people who deliver or sell drugs to people who subsequently overdose (Boecker 2015). In short, while drug sales have historically been treated as a nonviolent crime, this may

Beckett et al. TOWARD THE END OF MASS INCARCERATION?325

be changing. It is conceivable that bifurcation in the context of this potential reconcep-tualization of drug selling could amplify racial disproportionality, especially given the racial coding of comparatively innocent drug (and especially opiate) users as white (Tiger 2017; Netherland and Hansen 2016).

The analysis presented below offers a more comprehensive analysis of recently enacted criminal justice reforms that includes all types of both incarcerative and decar-cerative legislation. However, a substantial body of sociolegal scholarship suggests that a complete assessment of the bifurcation hypothesis should also include analysis of trends in criminal case processing. Institutional and sociolegal studies highlight the importance of shifting our analytic focus from “the highly visible politics of large-scale reform to the subterranean political processes that shape ground-level policy effects” (Hacker 2004, 243). Although legislative developments are potentially consequential, their institutional effects are powerfully shaped by the “street-level bureaucrats” who work in criminal legal institutions (Ulmer and Johnson 2017; Verma 2016; Lynch and Omori 2014; Bushway and Forst 2013; Johnson, Ulmer, and Kramer 2008; Maynard-Moody and Musheno 2003; Lynch 1998, 2016). These frontline workers tend to “empha-size the role demands that they feel are worthwhile and within a set of broad organiza-tional constraints, and will subvert or downplay the tasks and duties deemed unimportant or somehow problematic” (Lynch 1998, 844–45).

In the criminal justice context, the often-substantial gap between the “law on the books” and the “law in action” (Halliday et al. 2009; Silbey and Sarat 1987; Lipsky 1980) may result from the exercise of discretion by legal actors, which is both ubiquitous and consequential throughout the criminal justice process (Lynch 2016; Lynch and Omori 2014; Stuntz 2011; Davis 2008). Research shows that local norms and organiza-tional practices powerfully shape discretionary decision making and hence case out-comes (Ulmer and Johnson 2017; Lynch 2016; Verma 2016; Lynch and Omori 2014; Johnson, Ulmer, and Kramer 2008). For example, studies examining geographic varia-tion in the implementation of California’s three strikes law show that prosecutors align their actions with their local political and cultural climate (Chen 2014; Bowers 2001; Zimring, Hawkins, and Kamin 2001), thereby mitigating the intended effects of that law in some counties. Verma (2016) similarly finds that California counties’ responses to statewide policy shifts regarding the reduced use of prisons reflect what she calls “the law before,” namely, past organizational practices and (local) ideological commitments. Finally, Lynch’s (2016) analysis of drug case processing in three regionally distinct fed-eral courts shows that, although the federal government’s enactment of tough drug sen-tencing laws notably and uniformly enhanced prosecutors’ power to punish, prosecutors exercise this power in somewhat different ways to achieve somewhat different ends in locales characterized by diverse norms and organizational priorities.

In short, studies of legal discretion in the criminal justice context highlight the impor-tance of organizational practices and normative commitments in shaping institutional practice. To the extent that the sensibilities highlighted by the bifurcation hypothesis are widespread, we would expect to see trends in formal law and case processing that entail less serious penalties for nonviolent crimes but harsher punishments for those convicted of violent crimes. However, the literature on path dependence identifies an alternative set of considerations that may also influence legal practices and decision making. Path dependence refers to “the tendency for courses of political or social development to ‘gen-erate self-reinforcing processes’” (Pierson 2000, 810) that impede efforts to change direc-tion. As this literature shows, developments such as mass incarceration enhance institutional capacity and create vested interests that often seek to perpetuate favorable institutional arrangements.

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Studies provide numerous examples of such “positive policy feedback mechanisms” (Dagan and Teles 2014) in the context of mass incarceration. For example, private cor-porations that own and operate prisons (or profit from contracts with them), correc-tional officers’ unions, prosecutors, the bail industry, and even county clerks who depend on the collection of fees and fines often seek to block progressive criminal justice reform (Lynch 2016; Gottshalk 2015; Petersilia and Cullen 2014; Justice Policy Institute 2012; Mason 2012; Austin 2011; Page 2011), presumably in an effort to preserve jobs, resources, and authority. Similarly, legislators from rural communities that house prisons constitute an important voting bloc that seeks to obstruct the adoption of crimi-nal justice reforms (Thorpe 2015). Although these studies focus mainly on institutional actors’ efforts to block legislative reform, they also suggest that institutional actors are likely to exercise their discretion in ways that tend to preserve the increased jobs, resources, and authority that these actors have enjoyed as a result of mass incarceration (Lynch and Omori 2014).

In short, although statutory law often has cultural, political, and practical signifi-cance, institutional actors within the penal system powerfully shape its impact through their everyday decision making. Research identifies two main forces that often shape institutional decision making and practice: norms and ideological commitments on the one hand, and efforts to maintain or enhance institutional authority and resources on the other. To the extent that norms have been shifting in ways that are consistent with the bifurcation hypothesis, we would expect to see legislation and case outcomes that reflect an embrace of alternatives to incarceration for nonviolent offenses and an intensi-fication of the commitment to harsh punishment in response to violence. However, to the extent that resource considerations and institutional incentives drive potential shifts in on-the-ground decision making and case outcomes, shifts toward penal severity may be more evenly distributed across offense categories.

In theory, shifts toward penal severity in case processing outcomes may also reflect changes in case characteristics. Indeed, a recent study indicates that the increase in the number of prior convictions possessed by felony defendants (rather than a shift in prose-cutorial or judicial discretion) explains the growth in prison admissions that has taken place in Minnesota in recent years (King 2016). Of course, criminal records not only reflect criminal behavior but also institutional practices and decision making by legal actors. Moreover, the practice of treating prior convictions as a determinant of sentenc-ing outcomes and the weighting of those convictions are also discretionary. This is most obvious in states with indeterminate sentencing laws, where consideration of criminal history is largely informal. But it is also true in states that utilize sentencing grids that include defendants’ criminal histories as determinants of sentencing outcomes. As Bush-way and Forst (2013) argue, the setting of rules also involves legal discretion, albeit of a different type than that exercised by individual legal actors such as judges or prosecu-tors. And as Tonry (2016) emphasizes, the practice of basing sentencing decisions in large part on defendants’ criminal records is common in the United States but rare in the European context.

III. DATA AND METHODS

Many studies have analyzed trends in case processing to identify the causes of the prison buildup (Pfaff 2017; Travis, Western, and Redburn 2014; Raphael and Stoll 2009, 2013; PEW Center on the States 2012; Western 2006; Blumstein and Beck 1999). Such studies have examined trends in key case processing outcomes, including the arrest-to-crime

Beckett et al. TOWARD THE END OF MASS INCARCERATION?327

ratio, the admission-to-arrest ratio, sentence length, and time served. With one impor-tant exception, these studies conclude that the prison buildup was driven mainly by a rise in drug arrests, the increased likelihood that arrests for all types of felony crimes would trigger a prison admission, and increased time served, especially for violent offenses. By contrast, Pfaff (2017) argues that time served did not increase and therefore that tough sentencing laws are not a key driver of mass incarceration. Instead, he argues, the increased propensity of prosecutors to file felony charges, particularly in cases involving violence, was the primary driver of prison growth. However, the vast majority of studies using alternative methods to estimate trends in time served find that time served in prison has increased notably and that this trend has contributed importantly to penal expansion (see Beckett 2018 for an extended discussion of the methodological issues that appear to explain Pfaff’s anomalous findings). The apparent increase in time served through the mid-2000s is likely the product of shifts in both formal sentencing law and on-the-ground decision making by institutional actors, as well as the interaction between the two; as Lynch (2016) shows, harsh sentencing laws enhance prosecutorial power even when the majority of defendants do not receive the maximum allowable sentence.

While this literature has identified the main drivers of the prison buildup, little is known about trends in criminal justice processing in the current era during which incar-ceration rates fell modestly. Specifically, it is unclear how the police response to reported crimes, the likelihood that arrest will trigger prison admission, sentencing outcomes, and time served have changed since incarceration rates peaked in 2007, and how these responses may vary by offense type. Mapping trends in both sentencing law and case processing will enable a comprehensive assessment of the bifurcation hypothesis. It will also help explain why the imprisonment rate has fallen more modestly than would be predicted based on crime trends and the widespread enactment of decarcerative reforms. We focus on the period since incarceration rates peaked (in 2007) because we seek to understand the complex developments that characterize “late” mass incarceration, dur-ing which time many conservatives have embraced the criminal justice cause, the Great Recession occurred, and crime rates have continued to plummet. Below, we describe the data and methods used in the analyses.

A. LEGISLATIVE DEVELOPMENTS

The purpose of our analysis of legislative developments is to identify the nature and focus of sentencing-related statutory measures enacted since mass incarceration’s peak and to assess the claim that late mass incarceration is characterized by a new way of responding to crime that sharply differentiates between violent and nonviolent crime. We do not seek to evaluate the impact of recently enacted legislation on case outcomes. Rather, the analysis provides a qualitative assessment of the nature and direction of criminal justice reforms enacted since incarceration rates peaked in 2007.

Information about recent statutory reforms was taken from the State Sentencing and Corrections Legislation data set compiled by the National Conference of State Legisla-tures (NCSL). Information about measures enacted from 2007 to 2009 comes from Sig-nificant State Sentencing and Corrections Legislation reports published annually by NCSL; descriptions of session laws implemented between 2010 and 2014 were obtained through NCSL’s searchable online database. We also frequently accessed the final bill online to determine its intent and focus. These sources were cross-checked against, and supplemented with, a number of synthetic reports that summarize developments in crim-inal justice legislation (PEW Charitable Trusts 2016; Silber, Subramanian and Spotts

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2016; Subramanian and Delaney 2014; Subramanian and Moreno 2014; Lawrence 2013; Austin 2011; Porter 2011–2013, 2014, 2015; King 2008, 2009). These data encompass all fifty states.

Once the database was compiled, we identified provisions that appear to have been intended to reduce or enhance prison sentences or time served.3 For example, legislation that prohibits registered sex offenders from obtaining licenses that allow them to own and operate ice cream trucks were not included in the analysis; legislation that expands inmates’ capacity to earn credits toward early release was classified as a “back-end” measure intended to reduce time served. In order to render the scope of the analysis manageable, we included measures that were intended to affect the length of prison sen-tences and stays for felony (but not misdemeanor) crimes. Many provisions included in the analysis may or may not have an impact on prison sentences or time served. For example, many recent sentencing reforms authorized, but did not require, judges to impose more lenient sentences for nonviolent offenses. Similarly, some back-end reforms authorized parole board members to consider parole applicants’ involvement in educa-tional and other programming for people serving time for nonviolent crimes. Because we do not seek to assess the quantitative impact of these legislative provisions, but rather are interested in their intent, the uncertain impact of these measures on outcomes is not a concern.

Legislative provisions aimed at reducing sentences or time served were coded as decar-cerative; provisions intended to enhance sentences or time served were coded as incar-cerative. Measures that seek to affect the sentences imposed by judges were coded as “front-end,” while provisions that pertain to prison release and parole revocation deci-sions, and therefore could impact time served, were classified as “back-end.” We also coded the type(s) of offense(s) to which the legislation pertains in order to compare trends in the violent and nonviolent categories. The unit of analysis is the legislative pro-vision rather than the session law, as the majority of enacted laws contained multiple and substantively distinct provisions, often with diverse purposes. For example, Minne-sota’s 2013 Senate Bill 671 simultaneously expanded release opportunities for drug offenders and created a new mandatory minimum sentence for repeat sex offenders. Each distinct provision was coded according to the nature and direction of the reform implemented. In this case, the former provision was coded as “Decarcerative—Back End—Drug” while the latter provision was coded as “Incarcerative—Front End—Sex.”

B. CRIMINAL CASE PROCESSING

Our analytic strategy for identifying trends in criminal justice outcomes is inspired by the decomposition methodology that has been widely used to assess the relative importance of changes in practice and policy (as opposed to crime rates) during the prison buildup (e.g., Travis, Western, and Redburn 2014; Raphael and Stoll 2009, 2013; Western 2006; Blumstein and Beck 1999, 2005). The starting point for our analysis is the “iron law of prison populations” (Clear and Austin 2009), which holds that imprisonment rates are a function of two factors: prison admissions and the amount of time people spend in prison (i.e., time served). Each of these direct inputs has a number of determinants. Prison admis-sions, for example, may stem either from parole or probation revocation or from new court commitments to prison, which in turn are affected by crime and arrest rates, case character-istics, prosecutorial practices, and sentencing policy. Time served is largely determined by three factors: the sentence imposed, policies that govern the accumulation of “good time” credits, and parole board decision making (in states that have retained parole).4

Beckett et al. TOWARD THE END OF MASS INCARCERATION?329

As in other studies, we include information about crime rates as well as a series of case processing outcomes. These outcomes include the arrest-to-crime ratio, the prison admission-to-arrest ratio, sentence length, and time served. The arrest-to-crime ratio provides some sense of the strength/efficacy of the police response to reported crimes, while the admission-to-arrest ratio is potentially influenced by case characteristics, pros-ecutorial discretion, and sentencing policy. Although it is theoretically possible to sepa-rate the admission-to-arrest ratio into two constituent parts—the filing-to-arrest ratio and the admission-to-filing ratio (see Pfaff 2017)—national filing data are, unfortu-nately, insufficiently reliable and detailed to enable this type of analysis.5

We examine changes in outcomes from 2007 to 2014 (the most recent year for which National Corrections Reporting Program [NCRP] data are consistently available) in order to assess trends since incarceration rates peaked. We analyze trends in outcomes for the four main NCRP crime categories: violent crimes, property offenses, drug viola-tions, and public order crimes (99 percent of all admissions involve offenses that fall into one of these four categories). The most common offenses included in the public offense category are weapons violations and driving-under-the-influence (DUI).6 As a result, this category is arguably closer to the violent than the nonviolent categories. We analyze trends for these four broad offense categories and technical parole violations separately, for two reasons. First, outcomes may not be moving in parallel directions across these categories. Indeed, the bifurcation hypothesis predicts that responses to nonviolent crimes are becoming more lenient, while the opposite is happening for violent crimes. In addition, a change in the share of prison admissions due to minor offenses such as drug offenses can dramatically impact average sentence length and time served (Raphael and Stoll 2013).

C. CRIME AND ARREST DATA

Crime and arrest data are available through the Federal Bureau of Investigation’s Uni-form Crime Reports (UCR) (FBI n.d.) . Most city, county, state, and tribal law enforce-ment agencies provide information about arrested persons and crimes known to the police through the UCR. In 2012, the law enforcement agencies participating in the UCR program represented more than 270 million United States inhabitants, or 85.4 per-cent of the total population. All states and Washington, DC, are included in our analysis of national crime and arrest trends. Kentucky underreported its data to the UCR in 2007 and 2008 relative to subsequent years, so crime and arrest data for that state were taken from Crime in Kentucky—2007, published by the Kentucky State Police (n.d.) . Alabama arrest figures for the years 2011 to 2014 were extremely low compared to prior years, and the FBI did not include arrest data for Hawaii in 2007. We therefore used Alabama arrest data from the Alabama Criminal Justice Information Center in place of the UCR data for 2011 to 2014 (Alabama Criminal Justice Information Center 2012–2014, 2015), and 2007 Hawaii arrest data is from Crime in Hawaii 2007: A Review of Uniform Crime Reports (Fuatagavi and Perrone 2008). These data sources use the same variable definitions as the UCR.

UCR data identify twenty-eight different offenses, eight of which are considered com-paratively serious. Of these “index crimes,” four—murder and nonnegligent manslaugh-ter, rape, aggravated assault, and robbery—are categorized by UCR as violent, while another four—burglary, larceny-theft, motor vehicle theft, and arson—are classified as property crimes. We focus on these comparatively serious index crimes, all of which have the potential to become felony cases and therefore to trigger prison admission. We also include information about arrests for drug offenses other than marijuana possession

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(because marijuana possession arrests very rarely trigger prison admission),7 as well as weapons violations and DUIs, which are considered public order offenses and can also trigger felony charges.

D. PRISON ADMISSIONS, SENTENCES, AND TIME SERVED

Data regarding prison admissions, sentences imposed, and time served are available through the NCRP. NCRP data are individual-level, administrative data collected by the Bureau of Justice Statistics and include demographic information, offense type, sen-tence imposed, type of admission and type of release. The collection began in 1983 and is available through the Inter-University Consortium for Political and Social Research (ICPSR) at the University of Michigan.

Our analysis focuses on state prisons, where the majority of US inmates reside.8 In general, defendants convicted of felonies who are sentenced to more than twelve months of confinement serve their sentences in prison rather than jail. In some states, however, jail and prison systems are combined. Moreover, some states incarcerate defendants with a sentence of less than one year in state prisons.9 Given this complexity, we include inmates in our analyses if they were sentenced to one or more years of confinement (see also Raphael and Stoll 2013; PEW Center on the States 2012). Because California now requires that defendants with sentences of less than four years serve their sentences in county jails,10 its NCRP data omit people with sentences shorter than four years. Because inclusion of these data would systematically bias our results, California is there-fore excluded from the analyses presented below.

In order to check the reliability of the NCRP data, we compared state prison admission counts from the NCRP with information provided by state Departments of Corrections and data from the National Prisoner Statistics Program (NPSP). Although the NCRP term records data file contains records for all states, data quality varies significantly by state and over time. Thirteen states (Alaska, Arkansas, Connecticut, Delaware, Florida, Hawaii, Idaho, Louisiana, Maryland, Mississippi, Ohio, Vermont, and Virginia) were excluded due to missing data on key variables such as admission type, missing data, or concerns about the reliability of the data. Six other states (Kansas, Maine, Massachusetts, Montana, New Hampshire, and New Mexico) were missing several years of data near the start or end points of our analysis and therefore were not included. Finally, as noted above, California was also excluded. After these exclusions, the sample includes thirty states11 that submitted reliable data: Alabama, Arizona, Colorado, Georgia, Illinois, Indiana, Iowa, Kentucky, Michigan, Minnesota, Missouri, Nebraska, Nevada, New Jersey, New York, North Caro-lina, North Dakota, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, and Wyo-ming.12 This sample is regionally diverse and includes a significant number of small, medium, and large states with differing degrees of urbanization. Like other researchers ana-lyzing NCRP data from a similar number of states, we treat this sample as a window onto national trends (see also Travis, Redburn, and Western 2014; Raphael and Stoll 2009, 2013; PEW Center on the States 2012; Western 2006; Beck and Blumstein 1999, 2005).

Admission-to-Arrest Ratios: Prison admissions data include people admitted to prison in all four crime categories as well as for parole violations. When calculating the arrest-to-admission ratio, we include all states that are included in the NCRP sample and cal-culate the ratio for our four main offense categories.

Sentence Length: Criminal sentences influence how much time prisoners spend behind bars; they also serve as an important indicator of the judicial and legislative mood. For these reasons, we report findings regarding sentencing outcomes (see also Beck and

Beckett et al. TOWARD THE END OF MASS INCARCERATION?331

Blumstein 1999). Sentence length calculations are based on the maximum sentence imposed. For people convicted of more than one offense, sentencing data pertain to the offense that carries the longest possible sentence. Following US Sentencing Guidelines Commission practice, life sentences were converted to 470 months in order to calculate average sentence lengths.13 Death sentences were excluded from this analysis.

Time Served: Sometimes called length of stay (LOS), time served is surprisingly diffi-cult to measure. Time served is most directly captured by observing the time between the admission and release of actual cohorts of prisoners (see Pfaff 2017), but inmates with long and life sentences are rarely released from prison and are therefore undercounted by this observational measure. Indeed, Patterson and Preston (2008) found that the observational measure is the least accurate of the options available for measuring time served.

Several alternative methods have been used to estimate expected (as opposed to observed) time served. The first, utilized by Blumstein and Beck (1999; and in Travis, Western, and Redburn 2014), involves calculating the ratio of the prison population to admissions for particular offenses. A second, related technique involves calculating the reciprocal of the exit rate, that is, the ratio of the number of prisoners released to those serving time in prison in a given year (see Raphael and Stoll 2013; PEW Center on the States 2012). Although both of these measures have the advantage of including long-term and life-sentenced prisoners, they are valid only when admissions and releases are holding steady. When this is not the case, these methods also notably underestimate time served (Patterson and Preston 2008).

In light of these issues, we use the method for estimating time served that has been found to most closely approximate the gold standard of the life table: the growth-adjusted reciprocal of the exit rate (Patterson and Preston 2008). This method includes information about the exit rate in order to capture the impact of the growth in life sen-tences but also adjusts for fluctuations in prison admissions and releases. Specifically, we calculate the reciprocal of the exit rate, then adjust it to take change in the prison popu-lation into account. This correction involves including information regarding both the rate of growth and the difference between the mean age at exit and the mean age of the prison population (see Patterson and Preston 2008). The equation for estimated time served is as follows:

e0 ≈1:

0d½erðAD APÞ&

Our estimates of time served include pre- and postconviction incarceration (see also PEW Center on the States 2012). In estimating time served, we included people released from prison for any reason other than escape or transfer to another prison.

IV. FINDINGS: CRIMINAL JUSTICE POLICY AND PRACTICE IN LATE MASS INCARCERATION

A. LEGISLATIVE REFORM

Figure 1 provides an overview of legislative reforms related to criminal sentencing enacted from 2007 to 2014. As this figure shows, decarcerative reforms intended to reduce prison sentences and time served outnumbered incarcerative measures by a sub-stantial margin. Specifically, we identified a total of 372 decarcerative and

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0510152025303540

Alabama

Alaska

Arizona

Arkansas

California

Colorado

Connecticut

Delaware

Florida

Georgia

Hawaii

Idaho

Illinois

Indiana

Iowa

Kansas

Kentucky

Louisiana

Maine

Maryland

Massachusetts

Michigan

Minnesota

Mississippi

Missouri

Montana

Nebraska

Nevada

New Hampshire

New Jersey

New Mexico

New York

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

Pennsylvania

Rhode Island

South Carolina

South Dakota

Tennessee

Texas

Utah

Vermont

Virginia

Washington

West Virginia

Wisconsin

Wyoming

	Incarcerative		Decarcerative

Figure 1. State Sentencing Reforms by Type, 2007–2014.

129 incarcerative provisions, with the former outnumbering the latter by a ratio of nearly three-to-one. Moreover, this pattern was fairly consistent across the fifty states; only three states (Tennessee, South Dakota, and Utah) enacted more incarcerative than decarcerative provisions. It thus appears that the idea that states should endeavor to

Beckett et al. TOWARD THE END OF MASS INCARCERATION?333

reduce their prison populations has had significant traction in state legislatures since incarceration rates peaked in 2007.

At the same time, a clear majority of the decarcerative reforms were limited to nonvi-olent or nonserious offenses; very few states adopted measures intended to reduce sen-tences or prison stays for people convicted of violent or other serious crimes. Figure 2 shows the number of front-end sentencing provisions enacted by type and offense cate-gory. As this figure reveals, states enacted far more decarcerative legislative provisions aimed at reducing prison sentences for drug, property, or “nonserious” offenses than measures aimed at shortening sentences for people convicted of violent or sex offenses (169 vs. eleven). Incarcerative sentencing provisions were fewer in number but more evenly split across offense category: thirty-nine such measures targeted violent or sex offenses, while thirty-six were aimed at less serious crimes. Thus, although decarcerative front-end measures outnumbered incarcerative ones by a notable margin, very few tar-geted more serious offenses that carry relatively long prison sentences.

A similar and even more pronounced pattern can be discerned when we focus on back-end reforms that have the potential to affect length of stay. As Figure 3 shows, state-level efforts to reduce time served by facilitating early release and/or reducing prison admissions for technical parole violations have been quite popular, and they vastly outnumber measures intended to do the opposite (175 vs. thirty-seven). However, none of these decarcerative measures were specifically aimed at people convicted of vio-lent and other serious crimes. Although some decarcerative back-end reforms did not explicitly exclude people convicted of serious offenses, our sense is that most of these reforms will not, in fact, facilitate early release for most prisoners serving time for vio-lent crimes due to other constraints embedded in the legislation. For example, some measures included in this category were limited to juveniles sentenced as adults; others merely call upon departments of correction to develop a new policy for allocating good time credits.

In sum, although the legislative findings indicate a clear shift in favor of decarcerative reforms, they also confirm the claim that most recent reform measures are limited to people convicted of nonviolent, nonserious offenses (see Beckett, Reosti, and Knaphus 2016; Seeds 2016; Tonry 2016; Gottshalk 2015). They also provide additional confirma-tion that the draconian sentencing laws that contributed to the prison buildup, many of

180

170

160

150

140

130

120

110

100

Figure 2. Front-End Sentencing Reforms by Type and Offense Category, 2007–2014.

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100

Technical Violations Nonviolent Offenses		Violent and Public Not Offense Specific
		Order Offenses
	Incarcerative	Decarcerative

Figure 3. Back-End Release Reforms by Type and Offense Category, 2007–2014.

which pertain to violent offenses, have not been repealed (Tonry 2016). These findings are largely consistent with the bifurcation hypothesis, as legislatures generally limited decarcerative reforms to drug, property, and other “nonserious” offenses. Below, we assess whether criminal justice processing outcomes changed during this period, and if so, how.

B. TRENDS IN CRIME, ARRESTS, AND THE ARREST-TO-CRIME RATIO

The dramatic crime drop that began in the early 1990s has continued in recent years. Table 1 shows the change in the number of crimes known to the police and arrests for violent and property offenses from 2007 to 2014. Significant declines in crime took place across both of these offense categories. In the case of violent crime, the decline in arrests was nearly identical to the drop-off in the number of violent crimes known to the police. However, in the case of property crime, the number of arrests remained largely

Table 1. Change in Number of Crimes, Arrests, and Arrest-to-Crime Ratios, 2007 and 2014

								Arrest to
		Crimes			Arrests			Crime Ratio

			Percent			Percent
	2007	2014	Change	2007	2014	Change	2007	2014	Percent Change

Violent	1,408	1,198	-14.9%	510	437	-14.3%	.36	.36	.74%
Property	9,843	8,278	-15.9%	1,387	1,368	-1.4%	.14	.17	17.3%
Public Order	---	---	---	1,404	1,123	-20.0%	---	---	---
Drug	---	---	---	931	729	-21.7%	---	---	---

Source: Crime and arrest data were taken from the Uniform Crime Reports for all states with the following exceptions: 2007 arrest data for Kentucky were taken from Crime in Kentucky—2007, published by the Ken-tucky State Police; 2007 arrest data for Hawaii were taken from “Crime in Hawaii 2007: A Review of Uniform Crime Reports,” published by the Crime Prevention and Justice Assistance Division of the Attorney General, State of Hawaii; 2014 arrest data for Alabama were taken from Crime in Alabama 2014, published by the Ala-bama Law Enforcement Agency.

Note: Sample includes all US states and Washington, DC. Crimes include offenses known to the police, and crime and arrest numbers are in thousands.

Beckett et al. TOWARD THE END OF MASS INCARCERATION?335

unchanged. Specifically, although property crimes dropped by 15.9 percent, arrests for those offenses fell by just 1.4 percent. As a result, the proportion of felony property crimes that resulted in arrest grew fairly substantially (by 17.3 percent) from 2007 to 2014. It thus appears that this increase in police efficacy with respect to property crimes has partially offset the decarcerative impact of plummeting crime and arrest rates. In fact, we estimate that the increased propensity/capacity of the police to arrest property crime suspects generated more than 200,000 additional felony property crime arrests in 2014.14

Arrests for crimes for which offense-level data do not exist also declined during this period. In particular, drug arrests (excluding marijuana possession) fell by 21.7 percent, and arrests for public order crimes dropped by 20 percent. The number of felony cases that have the potential to end up on prosecutors’ desks has thus declined fairly dramati-cally in recent years, although the increase in the arrest-to-crime ratio for property crimes has partially offset the impact of this trend.

C. PRISON ADMISSION TRENDS

The prison admission-to-arrest ratio provides information regarding the share of (fel-ony) arrests that result in prison admission. Table 2 depicts the trend in the prison admission-to-arrest ratio for the four major offense categories and shows that the pro-portion of felony arrests that triggered prison admission increased for all offense types in the recent reform era. Perhaps most surprisingly, drug arrests were slightly more likely to trigger a prison sentence in 2014 than they were in 2007. The admission-to-arrest ratio for property crime also rose modestly. At the same time, the admission-to-arrest ratio rose quite substantially for both violent and public order offenses: the share of violent crime arrests that resulted in prison admission increased by 19 percent, while the propor-tion of public order arrests that triggered a prison sentence increased by 39 percent.

These findings indicate that a larger share of felony arrests of all types triggered a prison sentence in 2014 than in 2007. The substantive impact of these shifts is nontrivial. For example, we estimate that the change in the admission-to-arrest ratio for violent crime reported above generated 21,853 additional prison admissions in 2014. Similarly, the increase in the admission-to-arrest ratio for public order offenses meant that an esti-mated 22,486 prison admissions occurred that year that would not have taken place had the admission-to-arrest ratio remained constant.15 To put these figures in context, 28,171 fewer state prison admissions for new crimes took place in 2014 than in 2007;16

Table 2. Change in Prison Admissions and the Admission-to-Arrest Ratio, 2007–2014

		Prison Admissions			Admission-to-Arrest Ratio

	2007	2014	Percent Change	2007	2014	Percent Change

Violent	72,799	71,430	-1.9%	0.29	0.34	19.3%
Public Order	50,070	51,637	3.1%	0.06	0.08	38.7%
Property	80,379	78,698	-2.1%	0.09	0.10	7.6%
Drug	88,448	71,496	-19.2%	0.17	0.18	6.3%

Source: Authors’ analysis of NCRP and UCR data.

Notes: Sample includes thirty states. For Nevada, 2008 data were used. 2012 data for South Dakota and Ore-gon and 2013 data for Illinois, Michigan, and New Jersey were used in place of 2014 data. Drug arrest figures do not include arrests for possession of marijuana, which is rarely a felony offense. Public order admission-to-arrest ratios include three public order offenses for which both arrest and admissions data exist: DUI, weapons, and family offenses.

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this decline would have been nearly three times as large if the chances that an arrest for a violent or public order crime would trigger a prison sentence had not increased.

In summary, the share of arrests for drug or property crimes that resulted in prison admission increased modestly from 2007 to 2014, while the admission-to-arrest ratio for public order and violent offenses increased more substantially, by 39 and 19 percent, respectively. The latter increases, in particular, are doing significant work to bolster mass incarceration. Yet the fact that the admission-to-arrest ratio also increased for drug and property offenses suggests that something other than bifurcating sensibilities is afoot. In the following sections, we assess whether changes in sentencing and time served reflect a bifurcation sensibility, and whether they have helped to sustain high incarcera-tion rates.

D. SENTENCES AND TIME SERVED

Sentencing outcomes are potentially influenced by a number of factors, including case characteristics, prosecutorial filing and charging practices, judicial decision making, and sentencing policy. Below, we describe trends in the average sentences imposed from 2007 to 2014 for the four broad offense categories. The results presented in Table 3 indicate that average (maximum) sentence length increased for all four offense categories during the recent “reform” era. Specifically, over this eight-year period, average sentence length increased by approximately 7 percent for property, violent, and drug crimes and by 15 percent for public order offenses.

The fact that sentences increased for violent offenses is consistent with the bifurcation hypothesis, but the fact that they also increased for drug and property offenses is not. Moreover, the latter findings are surprising given the legislative trends described in Figure 2, which reveals concerted state efforts to reduce prison sentences for drug and property crimes. This pattern of results may stem from shifts in the exercise of prosecu-torial and judicial discretion in ways that are more consistent with the path dependence perspective rather than the emerging cultural sensibilities highlighted by the bifurcation hypothesis.

Table 3. Change in Average Sentence Length and Expected Time Served, 2007 and 2014

		Average Sentence			Expected Time Served

	2007	2014	Percent Change	2007	2014	Percent Change

Violent	10.1	10.8	7.3%	5.7	6.1	7.8%
Public Order	4.0	4.6	15.1%	1.9	2.3	23.6%
Property	4.8	5.2	7.0%	2.0	2.1	7.5%
Theft/Larceny	3.9	4.0	4.5%	1.6	1.8	14.6%
Burglary	6.2	6.5	4.5%	2.5	2.6	1.3%
Drug	5.3	5.7	7.6%	1.8	2.3	12.7%
Possession3	3.8	4.3	13.1%	1.6	1.7	6.1%
Trafficking4	7.2	7.5	3.3%	2.2	2.6	7.1%

Source: Authors’ analysis of NCRP data.

Notes: Sentence lengths and time served figures are shown in years. The full NCRP thirty-state sample was used with the following exceptions: Minnesota and Washington are excluded from sentence length calculations due to data limitations; Alabama, Arizona, Indiana, Pennsylvania, and West Virginia were excluded from drug possession calculations; and Indiana and Pennsylvania were excluded from the drug trafficking category due to lack of data availability. South Dakota and Oregon 2012 data were used in place of 2014 data, and Illinois, Michigan, and New Jersey 2013 data were used in place of 2014 data.

Beckett et al. TOWARD THE END OF MASS INCARCERATION?337

However, an alternative explanation for this puzzle is that sentences for drug and property crimes are growing because less serious cases, which carry lighter penalties, are being diverted from prison. For example, theft is the most minor type of felony property crime, and many states have taken active steps to reduce the number of people sent to prison for that offense by increasing the threshold that differentiates felony from misde-meanor theft (PEW Charitable Trusts 2016). An increase in sentence length for property crimes could reflect the fact that these comparatively minor property cases are increas-ingly likely to be diverted from prison while more serious property cases (i.e., burglary) remain in the prison system. Similarly, if many more drug possession cases were diverted from prison in 2014, the reported increase in drug sentences could reflect the fact that more of the drug cases that result in a prison sentence involve sales/trafficking as opposed to possession.

If such a change in the composition of cases were responsible for the upward trend in sentences, we would expect to see decreases in sentence length for less serious offenses (e.g., theft, possession) but not for more serious offenses (e.g., burglary, trafficking). Although plausible, this conjecture is not borne out by our findings. In fact, sentences increased more for people sent to prison for theft than for those convicted of more seri-ous property crimes (e.g., burglary). Similarly, sentences increased for both drug posses-sion and for drug trafficking. It thus does not appear that the increases in sentence length for property and drug crimes shown in Table 3 primarily reflect the diversion of less serious cases from prison and a resulting change in the composition of defendants being sentenced to prison.

In sum, average (maximum) sentences imposed by judges were slightly longer in 2014 than those imposed in 2007 for all offense types. Although our legislative findings sug-gest that this trend is unlikely to be a function of statutory shifts, it may be the result of a shift in the exercise of prosecutorial and/or judicial discretion as predicted by path dependence theorists. Whatever the cause, the fact that sentences are increasing for non-violent as well as violent crime is clearly inconsistent with the bifurcation hypothesis as well as with legislative trends.

Turning to time served, the results presented in Table 3 indicate that expected time served has continued to increase for people convicted of all offense types during the recent “reform” era, most dramatically for those convicted of public order and drug offenses (23.6 and 12.7 percent, respectively). It thus appears that the widespread enact-ment of the decarcerative “back-end” policy reforms identified in Figure 3 aimed at enabling prisoners, especially those serving time for nonviolent offenses, to earn “good time” credits and early release have not achieved their intended effects. Although the percentage increase in time served has been smaller for those convicted of violent crimes than those convicted of public order and drug offenses, the (average) number of months added to prison stays (i.e., eight) since mass incarceration’s peak has been greatest for this former category of prisoners. The fact that time served continued to increase throughout the reform era for all offense types, and not just for violent crimes, is gener-ally more consistent with the path dependence perspective rather than with the bifurca-tion hypothesis.

E. SUMMARY OF FINDINGS

Our findings indicate that state legislatures have enacted numerous measures to reduce prison admissions and stays, and that such measures notably outnumber those that seek to enhance prison time. Consistent with the bifurcation hypothesis, the majority of dec-arcerative reforms that have been enacted are aimed specifically at drug and property

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offenders. However, the (smaller number of ) incarcerative measures that have been enacted have not been limited to violent crime. These findings thus provide broad, if qualified, support for the bifurcation hypothesis. More generally, our findings regarding legislative trends are consistent with the argument that recent decarcerative reforms are limited in scope and do not entail repeal of the harsh sentencing laws that contributed to the prison buildup (Tonry 2016). As Clear and Frost (2013) note, the (increasingly) long sentences imposed on people convicted of violent offenses have a disproportionately large impact on prison populations, and our findings indicate that these sentences—and time served—have actually increased since mass incarceration’s peak.

On the other hand, the findings regarding trends in case processing do not provide clear and consistent evidence of a bifurcating response to crime, but instead are more consistent with the path dependence perspective. These findings show that the system response to property crimes and to all types of arrests has intensified in recent years. These incarcerative trends in case processing outcomes are bolded in Table 4 below, and include the following. First, the arrest-to-offense ratio for property crimes increased as drug arrests plummeted, and the former offset the impact of the latter.17 Second, the share of felony arrests that triggered a prison admission increased notably for all types of offenses. Finally, average sentence length and time served also increased for all offense types. In the case of time served, these increases were largest for public order and drug offenses, although the number of months added to the average sentence was greatest for violent crimes.

Overall, then, the results indicate that the criminal justice response to property crimes and drug arrests has not attenuated despite the widespread enactment of legislative mea-sures intended to accomplish this goal. Indeed, the system response to drug and property crimes has intensified despite the widespread adoption of reforms aimed at reducing pen-alties for these offenses. For violent and public order offenses, the share of arrests that result in prison admission, sentence length, and time served have also increased notably. These findings help explain why large drops in the rate of reported crimes have not pre-cipitated commensurate declines in the prison population.

IV. DISCUSSION AND CONCLUSION

Dramatically falling crime rates, the emergence of bipartisan support for criminal justice reform, and the widespread adoption of decarcerative legislative reforms have raised the specter of the end of mass incarceration. The idea that shifts in criminal justice discourse and policy might trigger significant changes in penal populations is entirely reasonable, as the history of mass incarceration suggests that pronounced shifts in political discourse

Table 4. Summary of Findings: Change in Crime, Arrests, and Case Outcomes, 2007–2014

	Violent	Public Order	Property	Drug

Offenses	-14.9%	---	-15.9%	---
Arrests	-14.3%	-20.0%	-1.4%	-21.7%
Arrest-to-Crime Ratio	.74%	---	17.3%	---
Admission-to-Arrest Ratio	19.3%	38.7%	7.6%	6.3%
Average Sentence	7.3%	15.1%	7.0%	7.6%
Expected Time Served	7.8%	23.6%	7.5%	12.7 %

Source: Authors’ analysis of UCR and NCRP data.

Note: See Tables 1–3 for details regarding sample and measurement.

Beckett et al. TOWARD THE END OF MASS INCARCERATION?339

and policy enactment can herald broad transformations of the criminal justice system that are largely independent of crime trends (Gottschalk 2007, 2015; Alexander 2010; Beckett 1997). However, the findings presented here suggest that rolling back the car-ceral state now that mass incarceration has come into being will be comparatively diffi-cult, despite the fact that crime rates have been plunging and the legislative will is, at least to some degree, present.

Our analysis assesses whether the contemporary criminal justice field is characterized by a bifurcated approach to criminal law and case processing in which the response to nonviolent offenses is attenuated while the response to violent crimes is intensified. The results of our analysis of legislative trends show that most decarcerative legislative reforms have been aimed at property and drug offenses, thus revealing a lack of commit-ment to repealing the harsh sentencing laws aimed at violent and serious crimes. These findings are consistent with the bifurcation hypothesis. Turning to case processing, how-ever, our findings show an across-the-board intensification of the system response to fel-ony arrests rather than a bifurcated one. It thus appears that, although political and media rhetoric consistent with bifurcation abounds (Beckett, Reosti, and Knaphus 2016) and states have (primarily) reformed laws pertaining to nonviolent crime to reduce reliance on prisons, the system response to all types of offenses has, counterintuitively, intensified since mass incarceration’s peak.

Although our data do not include direct measures of discretion or the dynamics that may be guiding its expression, the findings are more consistent with theoretical perspec-tives on path dependence rather than with the bifurcation hypothesis. Specifically, the fact that the system response to all types of offenses has intensified is consistent with the idea that enormous institutional interventions, such as mass incarceration, expand insti-tutional capacity and the motivation of the actors who inhabit those institutions to con-duct their work in ways that preserve jobs, authority, and resources. As Lynch and Omori (2014, 441) conclude, “In the context of those institutions that generate prisoners

. . . we should expect formidable resistance to retrenchment efforts”; court actors “and the organizational units in which they work are deeply invested in maintaining their legitimacy, stature and role in the justice system, so should be expected to ideologically and operationally adapt to changing policies in order to stave off diminution.” Although it is conceivable that changes in case characteristics, such as defendants’ criminal records, are changing in ways that also fuel the intensified system response to felony arrests (King 2016), the policies that govern the role of prior convictions and other case characteristics in sentencing are discretionary and could be modified in order to reduce the use of punishment. Future case studies that include information about case charac-teristics, filing decisions, plea bargaining processes and outcomes, and judicial decision making will be better situated to identify the precise mechanisms that explain heightened penal severity in the recent “reform” era.

Consistent with sociolegal scholars’ emphasis on the importance of on-the-ground legal decision making, our findings indicate that legislative trends and shifts in case pro-cessing outcomes are quite distinct: while the former largely conform to the bifurcation hypothesis, the latter do not, and instead reveal that the system response to property crimes and felony arrests of all types has continued to intensify. Until now, this intensifi-cation has been masked by an overall decrease in the incarcerated population: after decades of uninterrupted penal expansion, observers have understandably focused on recent, modest declines in the use of prisons and jails. However, the findings presented here show that these declines would be far larger were it not for the (largely invisible) intensification of the penal system’s response to all types of arrests in recent years. They

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also highlight the fact that recent decarcerative reform measures have not generally pro-duced their intended effects.

Most “pessimistic” observers who question whether the end of mass incarceration is near emphasize the limits of legislative reform strategies that target only nonviolent offenders (Tonry 2014, 2016; Gottshalk 2015). Our findings provide additional evidence that comprehensive reform remains elusive and that the sentences imposed on violent offenders continue to grow. Yet the findings presented here also suggest that, absent measures that effectively channel decision making and limit penal power in ways desired by criminal justice reformers, even comprehensive sentencing reform may be insufficient to end mass incarceration.

NOTES

Goodman, Page, and Phelps (2017) show that this support was not unanimous and that important sources of resistance persisted throughout this period. Similarly, Campbell and Schoenfeld (2013) and others (e.g., Lynch 2009) reveal state-level variation in the degree of carceral expansion and the historical antecedents of this variation. It is also clear, however, that criminal justice policy, media rhetoric, and case outcomes moved in a decidedly punitive direction across the country from the early 1980s through the early 2000s (Rapahel and Stoll 2013; Western 2006).

Calculations based on data from Carson (2018), Table 7, and FBI, Uniform Crime Reports (2007–2016) (FBI n.d.) . The overall incarceration rate (which includes jail inmates as well as state and federal prisoners) also fell far less (11.8 percent through 2015) than the crime rate during this period (see Kaeble and Glaze 2016, Table 4).

In states with combined prison/jail systems, we also included measures intended to alter jail sentences or stays.

Since the 1970s, fourteen states have largely or entirely abolished parole (Dharmapala, Gar-oupa, and Shepherd 2010).

National filing data are available from the National Center for State Courts (NCSC). Sixteen of the thirty-four states for which data are available are identified by NCSC as either overin-clusive, underinclusive, or both, and the NCSC is unable to provide information about the magnitude of the many errors contained in the data (personal communication, Kathryn Holt, Senior Court Research Analyst for the National Center for State Courts, May 12, 2017). Moreover, these data are not separated by offense type, which, given our interest in the bifur-cation hypothesis, renders them less useful here.

Other, far less common offenses categorized by NCRP as public order offenses include court offenses; commercialized vice, morals, and decency offenses; and liquor law violations.

According to the Bureau of Justice Statistics, less than one (.7) percent of all state prisoners were incarcerated as a result of a simple marijuana possession conviction in 1997 (cited in Office of National Drug Control Policy n.d., footnote 31). Marijuana laws have loosened con-siderably since that time.

Of the 2.2 million people incarcerated in the United States in 2014, 63.7 percent were housed in state prisons, while 26.7 percent and 9.6 percent were housed in local jails and federal prisons, respectively (Kaeble et al. 2015, Table 1).

In Indiana, North Carolina, and Ohio, defendants sentenced to six months or more are held in state prisons. In South Carolina, the Department of Corrections has jurisdiction over all adult defendants with sentences exceeding three months.

In 2011, the Supreme Court ruled in Brown v. Plata that overcrowded conditions in California state prisons violated the Eighth Amendment and ordered the removal of roughly 40,000 inmates from its prisons (Simon 2014).

In the past, researchers conducting similar reliability checks were compelled to exclude a larger number of states (Neal and Rick 2014). It appears that some of the issues with the NCRP data were recently corrected when term record files were constructed. For more details, see https://www.ncrp.info/LinkedDocuments/NCRP%20White%20Paper%20No%203.NCRP %20Computing%20Code.10%2018%202012.pdf (accessed December 14, 2017).

Beckett et al. TOWARD THE END OF MASS INCARCERATION?341

Five states included in the sample are missing data for one or two years between 2007 and 2014. In order to obtain as broad and inclusive a sample as possible, we included these states and utilized 2008 data for Nevada, 2012 data for Oregon and South Dakota, and 2013 data for Illinois, Michigan, and New Jersey.

This estimate is based on assessments of the average number of years between admission and death for inmates sentenced to life in prison (Schmitt and Konfrst 2015, endnote 52).

To generate this estimate, we multiplied the number of property crimes reported in 2014 by the arrest-to-crime ratio observed in our sample for 2007, then calculated the difference between the hypothetical and observed arrest numbers.

To generate these estimates, we multiplied the number of relevant arrests reported nationally in 2014 by the admission-to arrest-ratio observed in our sample for 2007, then calculated the difference between the hypothetical and observed admission numbers.

Figures taken from Carson (2015, Table 7) and Carson and Golinelli (2013, Table 1).

Although the data analyzed here do not illuminate why these trends occurred simultaneously, it seems possible that the decline in drug arrests freed up police resources that were then used to improve the police response to reported property crimes.

KATHERINE BECKETT is S. Frank Miyamoto Professor in the Department of Sociology and Professor in Law, Societies & Justice at the University of Washington, where she also serves as Director of the CLASS (Comparative Law and Society Studies) Center.

LINDSEY BEACH earned her Master’s in Sociology at the University of Washington, where she is currently pursuing her PhD with an emphasis on social control, mental health, and punishment.

EMILY KNAPHUS received her PhD in Sociology and certificate in sociolegal studies from the University of Washington in 2017. She is currently serving as Research Associate at the University of Washington’s Center for Evaluation and Research for STEM Equity.

ANNA REOSTI received her PhD from the Department of Sociology and certificate in Com-parative Law and Society Studies from the University of Washington in June of 2018. She is currently a Postdoctoral Weinberg Fellow in Legal Studies at the Center for Legal Stud-ies at Northwestern University. Her work focuses on the intersection of inequality, housing, sociolegal studies, and discrimination.

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Jan 16

Samuel Maxwell Samuel Maxwell (Jan 16 2020 6:54PM) : Mass Incarceration causes many outcomes, affecting more than just those imprisoned. Chenges entire demographics of neighborhoods.

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Jan 16

Samuel Maxwell Samuel Maxwell (Jan 16 2020 6:55PM) : Gone down but still very high.

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Jan 16

Samuel Maxwell Samuel Maxwell (Jan 16 2020 6:56PM) : 11% seems to be nothing in comparison to how big the imprisoned population is.

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Samuel Maxwell Samuel Maxwell (Jan 16 2020 6:59PM) : 2007-2014, incarceration rates dropped, but still not enough to bump US down in leaderboard.

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Samuel Maxwell Samuel Maxwell (Jan 16 2020 7:00PM) : People get less time for drug related crime but more for violent crime.

Jan 16

Samuel Maxwell Samuel Maxwell (Jan 16 2020 7:01PM) : Life w/ out parole is still largely put into action.

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Feb 28

Samuel Maxwell Samuel Maxwell (Feb 28 2020 10:41AM) : Racial Disparity

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Whole Image 0

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Paragraph 105 (Image 4) 0

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Whole Image 0

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Paragraph 106 0

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Paragraph 167 0

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Paragraph 167, Sentence 1 0

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Paragraph 168 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 168, Sentence 2 0

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Paragraph 169 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 169, Sentence 2 0

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Paragraph 191 0

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Paragraph 192 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 193 0

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Paragraph 198 (Image 11) 0

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Whole Image 0

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Paragraph 200 (Image 12) 0

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Whole Image 0

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Paragraph 201 0

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Paragraph 201, Sentence 1 0

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Paragraph 214 0

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Paragraph 214, Sentence 1 0

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Paragraph 215 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 216 0

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Paragraph 216, Sentence 1 0

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Paragraph 221 0

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Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 222 0

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Paragraph 222, Sentence 1 0

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Paragraph 277 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

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Paragraph 278 0

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Paragraph 289 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 290 0

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Paragraph 290, Sentence 1 0

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Paragraph 325 0

No paragraph-level conversations. Start one.

Paragraph 325, Sentence 1 0

No sentence-level conversations. Start one.

Paragraph 326 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 327 0

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Paragraph 327, Sentence 1 0

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Paragraph 328, Sentence 1 0

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Paragraph 328, Sentence 2 0

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Paragraph 338 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 339 0

No paragraph-level conversations. Start one.

Paragraph 339, Sentence 1 0

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Paragraph 402 0

No paragraph-level conversations. Start one.

Paragraph 402, Sentence 1 0

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Paragraph 403 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 404 0

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No sentence-level conversations. Start one.

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No paragraph-level conversations. Start one.

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No sentence-level conversations. Start one.

Paragraph 424 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 425 0

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Paragraph 425, Sentence 1 0

No sentence-level conversations. Start one.

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Paragraph 459 0

No paragraph-level conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Whole Image 0

No whole image conversations. Start one.

Paragraph 460 0

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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Paragraph 507, Sentence 1 0

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Paragraph 508 0

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Paragraph 509 0

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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No sentence-level conversations. Start one.

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Nonviolent

Violent and Public Order

Not Offense Specific

Incarcerative

Decarcerative